Method for the ground-based monitoring of ewf-type anomalies in a positioning satellite signal

ABSTRACT

The method of the invention, which is applicable, in particular, to making positioning signals from GPS and SBAS satellites reliable, consists in performing an instantaneous statistical analysis (of around 1 mn duration) of the correlation peak from the satellite signal receiver and in comparing it to a long-term (several hours) statistical analysis by choosing 5 points which are characteristic of the peak (prompt, ±0.044 and ±0.088). If the result of the comparison exceeds a given threshold, the corresponding signals are rejected.

[0001] The present invention relates to a method for the ground-basedmonitoring of EWF-type anomalies in a positioning satellite signal.

[0002] Currently, aircraft landing guidance systems are of the ILS type,but, for economic reasons, various States are looking to replace themwith GLS guidance systems that use information supplied by satellitenetworks, in particular GPS. In aircraft, the on-board part of theselanding approach guidance systems is of the MMR type that combines ILSsystems with GLS and MLS systems.

[0003] GLS systems would be the most economical, especially in view ofthe fact that GPS positioning can supply aircraft with the informationneeded for their navigation. The performance levels required fornavigation in cruise flight allow the GPS system to be used in anautonomous manner offering an accuracy of around 20 to 30 meters and anintegrity sufficient for the requirements. In the landing approachphase, where the required vertical precision is around 2 to 3 meters,the system is used in combination with a complementary ground-basedmeans that provides the information necessary to improve the precisionand makes the mechanisms available that allow the positioning integrityto be guaranteed.

[0004] Numerous studies have been undertaken to determine the sources ofthe positioning errors affecting GPS measurements. The intentionaldegradation of the measurements carried out at the satellites was, untilit was recently dropped, the main cause of errors on the distancemeasurements between the receiver and the satellites. Nevertheless, thecauses of measurement errors remain from the use of the system ofradiopropagation itself, in other words the delays resulting from thepropagation of radio waves through the atmospheric layers, as well asthe errors resulting from possible reflections known as multiple rays.The estimation of these errors and their communication by groundstations, which group two or more measurement receivers and a means ofradiocommunication, allows the user receiving this information tocorrect their own measurements and thus to implement an accuratedifferential positioning. There exist, however, other kinds of errorsthat cannot be eliminated by these differential systems, namely theerrors resulting from a degradation in the operation of the satellitenetwork which can generate measurement errors depending on the physicalcharacteristics of the receivers using these signals. For example, whenthe signal transmitted by a satellite is affected by anomalies known as“EWF3”, the interference alters the correlation mechanisms implementedby the receivers and falsifies the distance measurements in a way thatdepends on the high-frequency filtering analog characteristics of thereceiver and the intervals separating the correlation channels and,consequently, falsifies the determination of the position. Thesephenomena must be detected in order to guarantee the integrity of thedifferential positioning used for landing approach guidance by aircraft.To remedy this, two or more ground stations in the same reception zoneare employed so that, using differential measurements, these errors canbe eliminated or sufficiently attenuated. There exist, however, otherkinds of errors that cannot be eliminated by these differential systems,namely the errors due to the ephemereses providing the satellitepositions and the errors due to the interference affecting the signalstransmitted by the satellites. The errors due to the ephemereses arisefrom the fact that these are manually input by operators and that typingmistakes are always possible. The satellite positioning errors couldthus be several kilometers. In order to eliminate them, it suffices tocompare several consecutive values and eliminate the one that clearlydoes not fit.

[0005] When the signal transmitted by a satellite is affected byanomalies known as “EWF” (Evil Waveform), the interference distorts thecorrelation peak produced in the ground-based receivers, whichdistortion does not allow the correlation to be performed correctly andtherefore falsifies the determination of position. To remedy this, aworking group has proposed a method for monitoring the quality of asignal transmitted by a satellite in an article numbered WP-13 andentitled “Validation of Revised Signal Quality Monitoring Algorithms forDetecting C/A Code Evil Waveforms” which was presented in Toulouse,France, during the “GBAS Working Group Meeting” which was held from the20^(th) to 24^(th) Mar. 2000 as part of the conference “GlobalNavigation Satellite Systems Panel (GNSSP)”, this working group beingthe “Working Group B”. The method proposed in this article essentiallyconsisted in sampling, at precise points in real time, the correlationfunctions produced in GPS ground-based receivers, in comparing thesesampled values to the set values, and in declaring the received signalinvalid if the result of the comparison exceeded a certain threshold.This method uses precise assumptions about the characteristics of thedetector and the detection criteria are based on the instantaneousobservation of the shape of the correlation peak which entirelydetermines the definition of the receiver and the definition of thedetection algorithms. Another method would consist in systematicallysampling the correlation peak. This method is satisfactory in theory,but, in order to put it into practice, it would require material meansat an exorbitant cost. Indeed, an 18-satellite GPS system, for example,would necessitate 720 correlation channels which would remove anyeconomic advantage of the GPS system, a system which is supposed to beless costly to operate than the existing systems.

[0006] The subject of the present invention is a method for ground-basedmonitoring of the possible presence of anomalies, in particular of theEWF type, in a signal received from a GPS satellite, which method couldbe implemented with the minimum of material means possible at thereceiving station, without however risking the non-detection ofsignificant anomalies in the received signal.

[0007] The method of the invention, which is based on the measurement ofthe distortion of the correlation peak, consists in taking samples ofthe correlation peak which is produced during the processing of thesignal received from the satellite, in storing these samples over aninstantaneous sliding time window of at least around 1 minute duration,in storing these instantaneous windows over a period of at least severalhours so as to extract therefrom a statistically determined mean value,in comparing the contents of each instantaneous window to this meanvalue and, if the result is greater than a detection threshold, indeclaring that there is a significant interference affecting thereceived signal and in eliminating the latter.

[0008] The present invention will better understood upon reading thedetailed description of one embodiment, taken as a non-limiting exampleand illustrated by the appended drawing, in which the single FIGURE is adiagram explaining the weighting step implemented by the method of theinvention.

[0009] The method of the invention applies to a receiver receivingsignals transmitted by geographical positioning satellites, whichreceiver is commonly referred to as a GBAS (Ground-Based AugmentationSystem). This terrestrial receiver comprises an SQM (Signal QualityMonitor) function responsible for continuously monitoring the quality ofthe received signals and for warning when the quality is unacceptable inorder to reject those signals judged unsuitable for positioningmeasurements and therefore to avoid falsifying the measurements.

[0010] The ground-based station receiver delivers samples of thereceived signal correlation peak at the rate of two times per second,with a view to carrying out amplitude measurements in the “in phase”correlator. According to the invention, these samples are five in numberand taken at precise instants which are sufficiently characteristic ofthe correlation peak to determine its exact position with the minimumpossible number of samples. These instants are located in a conventionalmanner using relative values with respect to the period of the PNsequence clock frequency, known as “chip”. These values are takensymmetrically with respect to the correlation signal peak, the centralvalue being that of the maximum of the peak (called “prompt”), namely(in values of chip fractions): prompt, ±0.044, ±0.088.

[0011] In addition, both short-term and long-term statistical analysesare carried out on the correlation peaks originating from the signalsreceived from each of the satellites concerned, for each of theaforementioned five values, in order to obtain the individualstatistical characteristics of these values as a function of theconditions of reception of these signals at the ground-based receivingstation. Five standard deviation values σ_(i) (namely: σ_(−0.088),σ_(−0.044), σ_(prompt), σ_(0.044) and σ_(0.088)) and five mean valuesμ_(i) (namely: μ_(−0.088), μ_(−0.044), μ_(prompt), μ_(0.044) andμ_(0.088)) are thus calculated for each type of analysis (short-term andlong-term) and for each satellite concerned.

[0012] The short-term analyses are effected within a sliding time windowof at least around one minute duration, and the long-term analyseswithin a sliding time window of at least several hours duration,cumulating all the short-term analyses relating to this long-termwindow. A variable Δμ_(i) is then defined, such thatΔμ_(i)=μ_(i)(ct)−μ_(i)(λt) with μ_(i)(ct) being the value of μ for thesample of rank i considered from the peak relative to the short-termanalysis and μ_(i)(λt) the value of the same sample relative to thelong-term analysis. A weighted criterion sqm for the quality ofreception at each analysis period is then calculated, the criterionbeing given by the following relation: ${sqm} = \frac{\begin{matrix}{\left\lbrack \frac{\Delta \quad \mu_{- 0.088}}{s_{- 0.088}} \right\rbrack^{2} + \left\lbrack \frac{\Delta \quad \mu_{- 0.044}}{s_{- 0.044}} \right\rbrack^{2} +} \\{\left\lbrack \frac{\Delta \quad \mu_{prompt}}{s_{prompt}} \right\rbrack^{2} + \left\lbrack \frac{\Delta \quad \mu_{+ 0.044}}{s_{+ 0.044}} \right\rbrack^{2} + \left\lbrack \frac{\Delta \quad \mu_{+ 0.088}}{s_{+ 0.088}} \right\rbrack^{2}}\end{matrix}}{MDE}$

[0013] In this relation, MDE is a detection threshold analyticallydetermined so as to obtain a desired false alarm probability ratio (forexample, 7.2×10⁻⁸ for the OACI standard). If the value of sqm thuscalculated is greater than 1, the presence of an abnormal waveform, orEWF, is declared and, consequently, the signals received from thecorresponding satellite must be rejected.

[0014] It will be noted that the term (sqm)² follows a chi-squarestatistical law with four degrees of freedom.

[0015] With reference to the OACI standard, the equivalent of the Kffdcoefficient, which has a value of 5.26 according to this standard for adistribution with a false alarm probability of 7.2×10⁻⁸, has a value of5.36, in the case of the invention, for a statistical distributionfollowing the chi-square law. Accordingly, owing to the fact that thesqm criterion is weighted, MDE must have a value of 5.36 in order toobtain the same false alarm probability ratio.

[0016] A shift register 1 which receives, at one end, the stream 2 ofPRN codes of the signal received from a satellite is shown schematicallyin the single FIGURE. The stream of internal PRN codes generated in thereceiver at the ground-based reception station is indicated by an arrow3.

[0017] These internal codes have the values that the samples of thecorrelation peak should have at the aforementioned sampling instants(central point, ±0.044, ±0.088) if the received signals were notaffected by parasitic EWF. The internal codes corresponding to instants−0.088, −0.044, prompt, +0.044 and +0.088 are each sent to an input of aconvoluter, 4 to 8 respectively, whose other input respectively receivesthe following values: contents of the register for the instant −0.088,contents for the instant −0.044, difference of the contents of theregisters relative to the instants +0.044 and −0.044 (obtained by asubtractor 10), and contents for the instants +0.044 and +0.088. Inaddition, the contents of the register for the instant where the promptshould appear are sent to a convoluter 9.

[0018] The six resulting correlation channels at the output of theconvoluters 4 to 9 are respectively: I_(−0.088) and Q_(−0.088),I_(−0.044) and Q_(−0.044,) I_(Δ) and Q_(Δ) (“delta” mode) , I_(0.044)and Q_(0.044), I_(0.088) and Q_(0.088), I_(prompt) and Q_(prompt)(“point” mode). The “delta” and “point” mode channels are used to followthe corresponding satellite, and the four other channels are used forthe I and Q (in phase and in quadrature) measurements at the fourcorresponding sampling points of the correlation peak.

1. A method for the ground-based monitoring of EWF-type anomalies in apositioning satellite signal, characterized in that it consists intaking samples of the correlation peak which is produced during theprocessing of the received signal, in storing these samples over aninstantaneous sliding time window of at least around 1 minute duration,in storing these instantaneous windows over a period of at least severalhours so as to extract therefrom a statistically determined mean value,in comparing the contents of each instantaneous window to this meanvalue and, if the result is greater than a detection threshold, indeclaring that there is a significant interference affecting thereceived signal and in eliminating the latter.
 2. The method as claimedin claim 1, characterized in that the samples are five in number foreach correlation peak analyzed, and in that instants corresponding tothe appearance of the maximum of the peak, to ±0.044 chip and to ±0.088chip relative to the peak maximum are sampled.
 3. The method as claimedin claim 2, characterized in that the weighted criterion (sqm), whosepurpose is to determine the quality of the received signal, is given bythe relation: ${sqm} = \frac{\begin{matrix}{\left\lbrack \frac{\Delta \quad \mu_{- 0.088}}{s_{- 0.088}} \right\rbrack^{2} + \left\lbrack \frac{\Delta \quad \mu_{- 0.044}}{s_{- 0.044}} \right\rbrack^{2} +} \\{\left\lbrack \frac{\Delta \quad \mu_{prompt}}{s_{prompt}} \right\rbrack^{2} + \left\lbrack \frac{\Delta \quad \mu_{+ 0.044}}{s_{+ 0.044}} \right\rbrack^{2} + \left\lbrack \frac{\Delta \quad \mu_{+ 0.088}}{s_{+ 0.088}} \right\rbrack^{2}}\end{matrix}}{MDE}$

in which Δμ_(i)=μ_(i)(ct)−μ_(i)(λt), where μ_(i)(ct) is the value of μfor the sample of rank i considered from the peak relative to theshort-term analysis and μ_(i)(λt) is the value of the same samplerelative to the long-term analysis, σ_(i) is the standard deviation foreach of these samples and MDE is a detection threshold which isdetermined so as to obtain a desired false alarm probability ratio, andwhere the value of sqm thus calculated must exceed unity for thepresence of a significant interference to be declared.